Characterization And Thermal Modification Of Local Bentonite For Removal Of Zinc Ion From Aqueous Solution
Process Engineering Project Topics
Get the Complete Project Materials Now! »
The natural bentonite has small specific surface area and cation exchange capacity. As a result, the focus of this research was directed towards the modification of the surface properties of bentonite to maximize its adsorption capacity. To achieve this aim, the research study was carried out by two stages; (1) Thermal modification of Ethiopian bentonite and (2) characterization, adsorption performance evaluation and kinetics study of the modified Ethiopian bentonite for removal of Zn(II). Characterization of both the raw and thermally modified bentonite clay for specific surface area and cation exchange capacity, surface functional groups, crystallinity and differential thermal analysis were studied using Methylene blue test, FTIR, XRD, DSC respectively. The surface area was increased from 147.1 m2/g to 310.2 m2/g as modification temperature increases from 300oC to 500oC. The results obtained from x-ray diffraction showed that the mineral is composed of montmorillonite and other impurities such as quartz, feldspar, muscovite, cristobalite and hematite. The thermal stability of the bentonite was studied using differential scanning calorimetry and from the result, it was confirmed that thermally stable up to 500 ℃. The effect of time, initial Zn(II) concentration and adsorbent dosage were experimentally studied using RSM. The results revealed that the amount of adsorption of Zn(II) increases with increasing contact time and adsorbent dosage and decreasing with increasing Zn(II) concentration. The optimum design parameters were recorded 75mg/l, 60min and1g and the percentage removal at those conditions was 99.54%. The results revealed that Langmuir isotherm and pseudo second-order kinetics provided better fits of the data. Therefore, the modified bentonite provides the large surface area and adsorption capacity and can be successfully employed for the removal of Zn(II) from wastewater.
Subsurface Intelligence & Critical Mineral Exploration
Modern Geology projects now focus on Machine Learning in Mineral Targeting, Carbon Capture & Storage (CCS) Geologic Modeling, and Critical Mineral Systems (Lithium, REEs). If your research involves Hydrogeological Connectivity, Seismic Inversion, or Geotechnical Site Characterization, ensure your analysis follows the JORC or NI 43-101 reporting standards and utilizes robust 3D Subsurface Visualization and Geochemical Fingerprinting frameworks.
Be the First to Share On Social
RELATED TOPICS
277
Enjoying our content?
Don't miss out on new videos! Subscribe to our YouTube channel for more awesome content.
Subscribe Now!